Disassembly is an essential operation in many industrial activities including repair, remanufacturing and recycling. Disassembly tends to be manually carried out - it is labour intensive and usually inefficient. Disassembly requires high-level dexterity in manipulations and thereby can be more difficult to robotise in comparison to the tasks that have no physical contacts (e.g. computer visual inspection) or simple contacts (e.g. cutting, welding, pick-and-place). Robotic disassembly has the potential to improve the productivity of repair, remanufacturing, recycling, all of which have been recognised as key components of a more circular economy. The existing procedure and state-of-the-art techniques for disassembly automation usually require a comprehensive analysis of a disassembly task, correct design of sensing and compliance facilities, efficient task plans, and a reliable system integration. It is usually a complex, expensive and time-consuming process to implement a robotic disassembly system. This project will develop a self-learning mechanism to allow robots to learn disassembly tasks and the respective control strategies autonomously, by combining multidimensional sensing and machine learning techniques. This capability will help build a more plug-and-play disassembly automation system, and reduce the technical difficulties and the implementation costs of disassembly automation. It is expected the next generation industrial robotics can be adopted in more complex and uncertain tasks such as maintenance, cleaning, repair, remanufacturing and recycling, where many processes are contact-rich. Disassembly is a typical contact-rich task. The Principal Investigator envisages that self-learning robotic disassembly will provide key understandings and technologies that can be adopted to the automation of other types of contact-rich tasks in the future to encourage a wider adoption of robots in the UK industry.

The creation of new, 21st Century manufactured products gives us exciting possibilities. However, the number of complex devices and components that consist of one piece of a single material is negligible; almost all manufacturing involves the joining of materials. Joining technology is extensive, but is still challenged by novel designs and new advanced materials. Frequently, these needs could be met by soldering, where a low melting point alloy is introduced in liquid form into the joint, where it solidifies, making a bond. Many people will associate soldering with the electronics industry, where it is widely used, reliably, effectively and at low cost. Yet current soldering is not good at forming bonds with many materials, (for example metals with tenacious oxides and ceramics) and it does not form strong joints which can resist exposure to elevated temperatures where applications demand it. To do this may need an approach used for brazing (very much like soldering, but at higher temperature) of adding an element to the alloy, whose role is to chemically interact with surfaces and improve wetting when liquid and bonding once solidified. Adapting the terminology from brazing, this would be "active soldering". Such a process is not simple however. First we must identify the correct active elements, which may not be the ones used in brazing. These must produce sufficient reaction at low temperatures and be adapted to the materials being bonded. Secondly, a way to introduce a large enough amount of these elements into the solder is required. Solders are based on tin, which may react with the active elements itself if too large quantities are present. Finally, such joints that have been attempted have very poor mechanical properties, and these must be improved. To resolve these challenges, we will deposit the active elements (selected with the aid of thermodynamic modelling) onto a metallic carrier, a Ni or Cu sponge or foam, with fine (~0.5mm) pores, and infiltrate the Sn into this, creating a composite solder. This will keep the active elements and the Sn separate until soldering, when the Sn will begin to dissolve the foam and progressively release the active material to aid in bonding. The residual network of the foam structure across the joint seam will also be effective in increasing the joint strength. We will make and test these composite solders and the joints, and we will also probe the reactions occurring in great detail, to ensure we understand the key step of this new technology. Of immediate use, this approach will improve the strength of bonds achieved in current applications (such as in antennae, heat exchangers and semiconductor devices), give them higher temperature resistance in service and reduce the environmental impact of the process, by removing the need for polluting chemical fluxes or electroplating to prepare the joint and aid bonding. The benefits certainly do not stop there, as the technology would also allow new applications. For example, metals like stainless steel are brazed in vacuum at high temperature; achieving the same goal at lower temperatures and in air would be a much less expensive process. Low process temperatures save energy and cost; for example, some electroceramics (important for, e.g. capacitors) can be processed by cold sintering at temperatures as low as 200degC, but the advantages would be lost without low temperature means to join them in electronic devices. Advanced materials such as graphene also hold much promise in areas like touchscreens and circuitry, and a technique like that developed here would be an essential part of making this a reality. The simple, mass manufacturing nature of solder means that, with our research partners including end users and processors of solder materials, the scalability of the new method created, and the chances of realising these benefits, will be very high.

Methanol is an appealing energy vectors, with attractive volumetric and gravimetric energy values, storable in liquid phase at ambient conditions of pressure and temperature, and that can be used as fuel directly or converted into chemicals or gasoline. However, its production lacks a sustainable route. Thus, the METHASOL project aims to produce methanol through a sustainable and cost-effective process based on the selective visible light driven gas phase CO2 reduction, with a solar to methanol energy conversion efficiency of 5%. During 42 months, METHASOL will gather 14 partners from EU/Associated MS, China and the USA, including some of the world’s most recognized researchers on artificial photosynthesis, to achieve a ground-breaking combination of a CO2 reduction reaction (CO2RR) system based on Metal-Organic Framework (MOF) and a graphitic Carbon Nitride (g-CN) for photocatalytic oxygen evolution reaction (OER), through a Z-scheme heterojunction. Following the definition of the system specifications (WP1), a first set of materials for OER and CO2RR will be synthesised and their photocatalytic activity and stability will be screened (WP2). The most promising materials will be further analysed thanks to experimental characterisation and modelling (WP3), leading to guidelines used for designing an enhanced CO2RR and OER materials (WP4). The best systems will then be integrated through a Z-scheme heterojunction, either with or without a mediator, and tested in tailored reactors operating in the gas phase under different conditions (WP5). A complete sustainability analysis will be conducted (WP6) to ensure the clean production of methanol. The cooperation between European and Chinese research entities will be consolidated to last beyond the project lifetime through the creation of a common exploitation plan (WP7). Through its ambitious activities on photocatalyst developments for solar to methanol conversion, METHASOL will propose a new path for decarbonizing Europe.

Currently, both maritime and aviation sectors are lacking a systematic approach to collect and assess Human Factors information in normal and emergency conditions. There is also a lack of agreed methodology to assess human-related risks with the aim of influencing design and operation of aircraft and ships. Therefore, the research question being addressed in this project is “How to fully capture human elements and their interaction with the other system elements to enhance safety in maritime and aviation operations?” It is important to address Human Factors aspects in relation to risk-based design of system and operations in a measurable manner by taking the variation in human behaviour over time and the non-flexibility of machines into consideration. The main aim of SAFEMODE project is to develop a novel HUman Risk Informed Design (HURID) framework in order to identify, collect and assess Human Factors data to inform risk-based design of systems and operation. These aims have not been achieved previously at a desirable level due to the unavailability of systematically collected data and lack of cooperation between different transport modes. The focus will be to reduce risks for safety critical situations, (e.g. mid-air collisions, grounding, evacuation, runway excursions etc.) through the enhancement of human performance. This will be achieved through investigation of past accidents, incidents, near-misses, reports, data from everyday operations, including previously unknown uncertainties such as increasing levels of automation and increased number of drones in transportation. This information will be incorporated the HURID framework and tools and into SHIELD, the open data repository and the living database, that will be maintained and continuously updated.